• DocumentCode
    3474932
  • Title

    An adaptive learning control approach

  • Author

    Geng, Zheng ; Jamshidi, Mo ; Carroll, Robert ; Kisner, Roger

  • Author_Institution
    Intelligent Automation. Inc., Rockville, MD, USA
  • fYear
    1991
  • fDate
    11-13 Dec 1991
  • Firstpage
    1221
  • Abstract
    An adaptive learning control approach is proposed which combines a mechanism to improve the control input sequence as well as to improve the learning control scheme based on the knowledge learned about the unknown system and environment. The iterative learning control problem is treated from the 2D system point of view. A 2D model for a class of iterative learning control system is formulated. A learning gain estimator algorithm based on the 2D model is presented. The overall learning control system structure is given. The proposed learning control scheme does not require prior knowledge of the controlled system and has the ability to generalize the knowledge learned from one task operation to other tasks. This scheme can be applied to nonlinear system control problems. To demonstrate the feasibility of the proposed learning algorithm, simulation results on learning control for a three-water-tank system are given. The results show an excellent learning performance, even for nonrepetitive tasks
  • Keywords
    adaptive control; iterative methods; learning systems; multidimensional systems; 2D system; adaptive learning control; iterative learning control; nonlinear system control; three-water-tank system; Adaptive control; Automatic control; Control system synthesis; Control systems; Error correction; Iterative algorithms; Nonlinear control systems; Nonlinear systems; Programmable control; Robotics and automation; Three-term control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
  • Conference_Location
    Brighton
  • Print_ISBN
    0-7803-0450-0
  • Type

    conf

  • DOI
    10.1109/CDC.1991.261567
  • Filename
    261567